Why do the number of maps and number of clusters differ?

This actually depends on your parameters. First remember that the segmentation is mainly two steps: a mathematical clustering, followed by some temporal processings.

The
first step of the Segmentation gives us "clusters", and they are the
right amount, so requesting 10 clusters will yield, well, 10 clusters...

Now
the second step (temporal processings) will alter this state of
affairs: requesting a Sequentialization of clusters will give us more
segments than clusters, and conversely rejecting small segments will
remove some. Combining both trends, the final number of segments is most
of the time different from the number of clusters...

Note:
there is a kind of semantic difference between a "cluster" and a
"segment". A cluster is something out of the Clustering algorithm, a
segment is a cluster with some temporal and physiological meaning.

What are these cryptic numbers in the segmentation file names, like ".08.(12).seg"?

This is the consequence of the previous point: the number of
requested clusters and the number of final segments might differ
according to your parameters. So the first number, here .08, stands for the number of clusters, and the second number, here .(12), stands for the resulting number of segments.

Why I get a message "Not enough TFs for the requested amount of clusters"

You need a minimum amount of samples (read: Time Frames) to run the segmentation:

The Clustering itself needs at least n TFs for a maximum of n clusters.

The computation of the KL quality measure needs one neighbor on each side, therefore for n clusters, you need at least n + 1 TFs.

(Well, there also are some side effects if (Min. requested segments) is 1, but Cartool will tell you the real limits anyway).

Fitting Maps: How do I specify groups with different number of subjects / files?

You
may have different number of files in your groups, f.ex. 50 subjects
and 10 patients. But currently, Cartool does not allow you to fit groups
of different sizes, as the output matrix of variables would be missing
some parts.

You can however bypass this limitation by doing the following steps:

Fit 1 group at a time

In the Statistics dialog, drop every .scv files generated by the above fittings

Check you have all your groups together, then don't forget not to use paired tests, but only unpaired!

You
can actually fit together groups of the same size: f.ex. for 4 groups
with 50, 10, 50 and 10 files, you can fit groups 1 and 3 together, then
groups 2 and 4.